Modelling sustainable international tourism demand to the Brazilian Amazon

The Amazon rainforest is one of the world’s greatest natural wonders and holds great importance and significance for the world’s environmental balance. Around 60% of the Amazon rainforest is located in the Brazilian territory. The two biggest states of the Amazon region are Amazonas (the upper Amazon) and Pará (the lower Amazon), which together account for around 73% of the Brazilian Legal Amazon, and are the only states that are serviced by international airports in Brazil’s North region. The purpose of this paper is to model and forecast sustainable international tourism demand for the states of Amazonas, Pará, and the aggregate of the two states. Economic progress of the region has been achieved at a cost of destroying large areas of the Amazon rain forest. In this scenario, the tourism industry would seem to have the potential to contribute to sustainable economic development in the North region of Brazil. The paper presents unit root tests for monthly and annual data, estimates alternative time series models and conditional volatility models of the shocks to international tourist arrivals, and provides forecasts for 2006 and 2007.forecasting;conditional volatility models;Brazilian Amazon;international tourism demand;time series modelling

Time Series Modelling of Tourism Demand from the USA, Japan and Malaysia to Thailand

Even though tourism has been recognized as one of the key sectors for the Thai economy, international tourism demand, or tourist arrivals, to Thailand have recently experienced dramatic fluctuations. The purpose of the paper is to investigate the relationship between the demand for international tourism to Thailand and its major determinants. The paper includes arrivals from the USA, which represents the long haul inbound market, from Japan as the most important medium haul inbound market, and from Malaysia as the most important short haul inbound market. The time series of tourist arrivals and economic determinants from 1971 to 2005 are examined using ARIMA with exogenous variables (ARMAX) models to analyze the relationships between tourist arrivals from these countries to Thailand. The economic determinants and ARMA are used to predict the effects of the economic, financial and political determinants on the numbers of tourists to Thailand.

GFC-Robust Risk Management Strategies under the Basel Accord

A risk management strategy is proposed as being robust to the Global Financial Crisis (GFC) by selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models. The robust forecast is based on the median of the point VaR forecasts of a set of conditional volatility models. This risk management strategy is GFC-robust in the sense that maintaining the same risk management strategies before, during and after a financial crisis would lead to comparatively low daily capital charges and violation penalties. The new method is illustrated by using the S&P500 index before, during and after the 2008-09 global financial crisis. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria. The median VaR risk management strategy is GFC-robust as it provides stable results across different periods relative to other VaR forecasting models. The new strategy based on combined forecasts of single models is straightforward to incorporate into existing computer software packages that are used by banks and other financial institutions.Value-at-Risk (VaR);daily capital charges;optimizing strategy;robust forecasts;violation penalties;global financial crisis;Basel II Accord;aggressive risk management strategy;conservative risk management strategy

What Happened to Risk Management During the 2008-09 Financial Crisis?

When dealing with market risk under the Basel II Accord, variation pays in the form of lower capital requirements and higher profits. Typically, GARCH type models are chosen to forecast Value-at-Risk (VaR) using a single risk model. In this paper we illustrate two useful variations to the standard mechanism for choosing forecasts, namely: (i) combining different forecast models for each period, such as a daily model that forecasts the supremum or infinum value for the VaR; (ii) alternatively, select a single model to forecast VaR, and then modify the daily forecast, depending on the recent history of violations under the Basel II Accord. We illustrate these points using the Standard and Poor’s 500 Composite Index. In many cases we find significant decreases in the capital requirements, while incurring a number of violations that stays within the Basel II Accord limits.risk management;violations;conservative risk strategy;aggressive risk strategy;value-at-risk forecast

"Precious Metals-Exchange Rate Volatility Transmissions and Hedging Strategies"

This study examines the conditional volatility and correlation dependency and interdependency for the four major precious metals (that is, gold, silver, platinum and palladium), while accounting for geopolitics within a multivariate system. The implications of the estimated results for portfolio designs and hedging strategies are also analyzed. The results for the four metals system show significant short-run and long-run dependencies and interdependencies to news and past volatility. These results have become more pervasive when the exchange rate and FFR are included. Monetary policy also has a differential impact on the precious metals and the exchange rate volatilities. Finally, the applications of the results show the optimal weights in a two-asset portfolio and the hedging ratios for long positions.

A decision rule to minimize daily capital charges in forecasting value-at-risk

Under the Basel II Accord, banks and other Authorized Deposit-taking Institutions (ADIs) have to communicate their daily risk estimates to the monetary authorities at the beginning of the trading day, using a variety of Value-at-Risk (VaR) models to measure risk. Sometimes the risk estimates communicated using these models are too high, thereby leading to large capital requirements and high capital costs. At other times, the risk estimates are too low, leading to excessive violations, so that realised losses are above the estimated risk. In this paper we propose a learning strategy that complements existing methods for calculating VaR and lowers daily capital requirements, while restricting the number of endogenous violations within the Basel II Accord penalty limits. We suggest a decision rule that responds to violations in a discrete and instantaneous manner, while adapting more slowly in periods of no violations. We apply the proposed strategy to Standard & Poor’s 500 Index and show there can be substantial savings in daily capital charges, while restricting the number of violations to within the Basel II penalty limits.value-at-risk;daily capital charges;optimizing strategy;risk forecasts;endogenous violations;frequency of violations

Precious Metals-Exchange Rate Volatility Transmissions and Hedging Strategies

This study examines the conditional volatility and correlation dependency and interdependency for the four major precious metals (that is, gold, silver, platinum and palladium), while accounting for geopolitics within a multivariate system. The implications of the estimated results for portfolio designs and hedging strategies are also analyzed. The results for the four metals system show significant short-run and long-run dependencies and interdependencies to news and past volatility. These results have become more pervasive when the exchange rate and FFR are included. Monetary policy also has a differential impact on the precious metals and the exchange rate volatilities. Finally, the applications of the results show the optimal weights in a two-asset portfolio and the hedging ratios for long positions.